Optimizing a bi-objective multi-period fish closed-loop supply chain network design by three multi-objective meta-heuristic algorithms
نویسندگان
1 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
2 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
4 Tecnologico de Monterrey, Escuela de Ingenieríay Ciencias, Puebla, Mexico.
doi
10.24200/sci.2021.57930.5477چکیده
Attention to a food Supply Chain (SC) has increased recently due to population growth and increased demand for food. Aquaculture development is advantageous as fish is a crucial constituent of the food basket of households. This study first presents a new bi-objective and multi-period mathematical model of a fish Closed-Loop Supply Chain (CLSC). The model is addressed by utilizing the Multi-Objective Keshtel Algorithm (MOKA), Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Multi-Objective Simulated Annealing (MOSA). The Taguchi method is employed to tune these metaheuristics to attain superior performance, and the ε-constraint method is used in solving small-sized problems to validate them. The results show that the exact method cannot solve large-sized problems.The solutions are compared in terms of different performance metrics. Using the ‘Filtering/Displaced Ideal Solution’ (F/DIS) method, NSGA-II and MOKA with a direct distance of 0.4228 and 0.8976 have the first and second performance ranks, respectively. Also, a case study including a trout CLSC in the north of Iran is investigated. The results and the case study show that the developed model can be applied to the proposed solution approach.
